Alumna: Nicole Muñoz
Profesor: Víctor Macías
Ayudante: Gabriel Cabrera

Pregunta 2

Librarías

library(quantmod)
library(dplyr)
library(plotly)
library(gridExtra)
library(tidyverse)
library(tidyquant)
library(forcats)
library(devtools)

Función

acciones <- c("AAPL","MSFT")
data <- tq_get(acciones,
               get = "stock.prices",
               from = "2000-01-01",
               to  = "2018-08-30",
               periodicity = "monthly")
data <- data.frame(data$symbol, data$date, data$close)
data <- data%>%rename(accion=data.symbol,
                      fecha=data.date,
                      precio=data.close)
finance = function(x,return=c('yes','no'),plot=c('type 1','type 2'),normal=c('yes','no')){
  
  #retornos log
  if (return=='yes'){
    retornoslog <- x %>%
      group_by(accion) %>%
      tq_transmute(select = precio,
                   mutate_fun = periodReturn,
                   period = "monthly",
                   type = "log",
                   col_rename = "retornos")
    dataA <- subset(retornoslog, accion=="AAPL")
    dataM <- subset(retornoslog, accion=="MSFT")
    dataA <- dataA %>% mutate(retcumA = cumsum(retornos))
    dataM <- dataM %>% mutate(retcumM = cumsum(retornos)) 
    
    #grafico 11:retornos log
    ifelse(plot=='type 1',
           g11 <- plot_ly(dataA, x = ~fecha) %>%
             add_lines(y = ~dataA$retornos, name = "APPLE", line = list(color = 'rgb(19,135,171)', width = 2)) %>% 
             add_lines(y = ~dataM$retornos, name = "MICROSOFT", line = list(color = 'rgb(153,171,254)', width = 2)) %>%
             layout(
               title = "RETORNOS (logarítmicos) APPLE & MICROSOFT",
               xaxis = list(
                 rangeselector = list(
                   buttons = list(
                     list(
                       count = 3,
                       label = "3 mo",
                       step = "month",
                       stepmode = "backward"),
                     list(
                       count = 6,
                       label = "6 mo",
                       step = "month",
                       stepmode = "backward"),
                     list(
                       count = 1,
                       label = "1 yr",
                       step = "year",
                       stepmode = "backward"),
                     list(
                       count = 1,
                       label = "YTD",
                       step = "year",
                       stepmode = "todate"),
                     list(step = "all"))),
                 
                 rangeslider = list(type = "Fecha")),
               yaxis = list(title = "Retornos")),
           
           ifelse(
             plot=='type 2',
                  g12 <- plot_ly(dataA, x = ~fecha) %>%
                    add_lines(y = ~dataA$retcumA, name = "APPLE", line = list(color = 'rgb(19,135,171)', width = 2)) %>% 
                    add_lines(y = ~dataM$retcumM, name = "MICROSOFT", line = list(color = 'rgb(153,171,254)', width = 2)) %>%
                    layout(
                      title = "RETORNOS ACUMULADOS (logarítmicos) APPLE & MICROSOFT",
                      xaxis = list(
                        rangeselector = list(
                          buttons = list(
                            list(
                              count = 3,
                              label = "3 mo",
                              step = "month",
                              stepmode = "backward"),
                            list(
                              count = 6,
                              label = "6 mo",
                              step = "month",
                              stepmode = "backward"),
                            list(
                              count = 1,
                              label = "1 yr",
                              step = "year",
                              stepmode = "backward"),
                            list(
                              count = 1,
                              label = "YTD",
                              step = "year",
                              stepmode = "todate"),
                            list(step = "all"))),
                        
                        rangeslider = list(type = "Fecha")),
                      
                      yaxis = list(title = "Retornos"))
           )#ifelse dentro de los graficos
    )#fin ifelse graficos 
  
    jlog = by(retornoslog,retornoslog$accion,
              function(x){
                n=length(x$retornos)
                mean = sum(x$retornos)/n
                skewness = ((sum(x$retornos-mean)^3)/n)/((sum(x$retornos-mean)^2)/n)^(3/2)
                kurtosis = ((sum(x$retornos-mean)^4)/n)/((sum(x$retornos-mean)^2)/n)^2
                JB = n*(((skewness^2)/6)+(((kurtosis-3)^2)/24))
                j = paste('p-value =',1 - pchisq(JB,df = 2),ifelse(1 - pchisq(JB,df = 2)<0.05,
                                                                   ', se rechaza la hipotesis nula de normalidad para los retornos de Apple',
                                                                   ', no se rechaza la hipotesis nula de normalidad para los retornos de Microsoft'))})
    }#fin primer if si return=yes
  #retornos aritmeticos
  else if (return=='no'){
    retornosimple <- x %>% 
      group_by(accion) %>%
      tq_transmute(select = precio,
                 mutate_fun = periodReturn,
                 period = "monthly",
                 type = "arithmetic",
                 col_rename = "retornos")
    dataA1 <- subset(retornosimple, accion=="AAPL")
    dataM1 <- subset(retornosimple, accion=="MSFT")
    dataA1 <- dataA1 %>% mutate(retcumA = cumsum(retornos))
    dataM1 <- dataM1 %>% mutate(retcumM = cumsum(retornos))
    
    
    ifelse(plot=='type 1',
           g21 <- plot_ly(dataA1, x = ~fecha) %>%
             add_lines(y = ~dataA1$retornos, name = "APPLE", line = list(color = 'rgb(19,135,171)', width = 2)) %>% 
             add_lines(y = ~dataM1$retornos, name = "MICROSOFT", line = list(color = 'rgb(153,171,254)', width = 2)) %>%
             layout(
               title = "RETORNOS (aritméticos) APPLE & MICROSOFT",
               xaxis = list(
                 rangeselector = list(
                   buttons = list(
                     list(
                       count = 3,
                       label = "3 mo",
                       step = "month",
                       stepmode = "backward"),
                     list(
                       count = 6,
                       label = "6 mo",
                       step = "month",
                       stepmode = "backward"),
                     list(
                       count = 1,
                       label = "1 yr",
                       step = "year",
                       stepmode = "backward"),
                     list(
                       count = 1,
                       label = "YTD",
                       step = "year",
                       stepmode = "todate"),
                     list(step = "all"))),
                 
                 rangeslider = list(type = "Fecha")),
               
               yaxis = list(title = "Retornos")),
           ifelse(plot=='type 2',
                  g22 <- plot_ly(dataA1, x = ~fecha) %>%
                    add_lines(y = ~dataA1$retcumA, name = "APPLE", line = list(color = 'rgb(19,135,171)', width = 2)) %>% 
                    add_lines(y = ~dataM1$retcumM, name = "MICROSOFT", line = list(color = 'rgb(153,171,254)', width = 2)) %>%
                    layout(
                      title = "RETORNOS ACUMULADOS (aritméticos) APPLE & MICROSOFT",
                      xaxis = list(
                        rangeselector = list(
                          buttons = list(
                            list(
                              count = 3,
                              label = "3 mo",
                              step = "month",
                              stepmode = "backward"),
                            list(
                              count = 6,
                              label = "6 mo",
                              step = "month",
                              stepmode = "backward"),
                            list(
                              count = 1,
                              label = "1 yr",
                              step = "year",
                              stepmode = "backward"),
                            list(
                              count = 1,
                              label = "YTD",
                              step = "year",
                              stepmode = "todate"),
                            list(step = "all"))),
                        
                        rangeslider = list(type = "Fecha")),
                      
                      yaxis = list(title = "Retornos"))
                  )#fin ifelse grafico tipo 2
           ) #fin primer ifelse grafico tipo 1
    
    j_arit= by(retornosimple,retornosimple$accion,
               function(x){
                 n=length(x$retornos)
                 mean = sum(x$retornos)/n
                 skewness = ((sum(x$retornos-mean)^3)/n)/((sum(x$retornos-mean)^2)/n)^(3/2)
                 kurtosis = ((sum(x$retornos-mean)^4)/n)/((sum(x$retornos-mean)^2)/n)^2
                 JB = n*(((skewness^2)/6)+(((kurtosis-3)^2)/24))
                 j = paste('p-value =',1 - pchisq(JB,df = 2),
                           ifelse(1 - pchisq(JB,df = 2)<0.05,
                                  ', se rechaza la hipotesis nula de normalidad para los retornos de Apple',
                                  ', no se rechaza la hipotesis nula de normalidad para los retornos de Microsoft'))})
    }#fin else if retornos=no
  
  #debemos general el resultado normal==no y dado que en ambos casos se realiza el test, programamos la salida:
  no="Se realizó test de Normalidad, ocultando su resultado"
  
  #debemos generar todas las posibles salidas
  ifelse(return=="yes"& plot=='type 1' & normal=="yes",return(list(g11,jlog)),
         ifelse(return=='yes' & plot=='type 2' & normal=="yes",return(list(g12,jlog)),
                ifelse(return=='yes' & plot=='type 1' & normal=="no",return(list(g11,no)),
                       ifelse(return=='yes' & plot=='type 2' & normal=="no",return(list(g12,no)),
                              ifelse(return=='no' & plot=='type 1' & normal=="yes",return(list(g21,j_arit)),
                                     ifelse(return=='no' & plot=='type 2' & normal=="yes",return(list(g22,j_arit)),
                                            ifelse(return=='no' & plot=='type 1' & normal=="no",return(list(g21,no)),
                                                   ifelse(return=='no' & plot=='type 2' & normal=="no",return(list(g22,no))))))))
                
         ))
  
  
  }#fin funcion

Resultados

finance(data,"yes","type 1","yes")
[[1]]


[[2]]
retornoslog$accion: AAPL
[1] "p-value = 0 , se rechaza la hipotesis nula de normalidad para los retornos de Apple"
--------------------------------------------------------- 
retornoslog$accion: MSFT
[1] "p-value = 0 , se rechaza la hipotesis nula de normalidad para los retornos de Apple"
finance(data,"no","type 1","yes")
[[1]]


[[2]]
retornosimple$accion: AAPL
[1] "p-value = 0 , se rechaza la hipotesis nula de normalidad para los retornos de Apple"
--------------------------------------------------------- 
retornosimple$accion: MSFT
[1] "p-value = 0 , se rechaza la hipotesis nula de normalidad para los retornos de Apple"
finance(data, "yes", "type 2", "yes")
[[1]]


[[2]]
retornoslog$accion: AAPL
[1] "p-value = 0 , se rechaza la hipotesis nula de normalidad para los retornos de Apple"
--------------------------------------------------------- 
retornoslog$accion: MSFT
[1] "p-value = 0 , se rechaza la hipotesis nula de normalidad para los retornos de Apple"
finance(data, "no", "type 2", "yes")
[[1]]


[[2]]
retornosimple$accion: AAPL
[1] "p-value = 0 , se rechaza la hipotesis nula de normalidad para los retornos de Apple"
--------------------------------------------------------- 
retornosimple$accion: MSFT
[1] "p-value = 0 , se rechaza la hipotesis nula de normalidad para los retornos de Apple"

Pregunta 3


---
output: 
  html_notebook:
    theme: yeti
---
```{r, include=FALSE}
htmltools::tagList(rmarkdown::html_dependency_font_awesome())
```




<head>
<button type="button" class="btn btn-primary btn-lg btn-block"><h1><b><i class="fab fa-github"></i> TAREA 5</b></h1></button>
<br>
<div class="alert alert-dismissible alert-info">
  <button type="button" class="close" data-dismiss="alert">&times;</button>
  <strong>Alumna:</strong> Nicole Muñoz <br>
  <strong>Profesor:</strong> Víctor Macías <br>
  <strong>Ayudante:</strong> Gabriel Cabrera <br>
  
</div>
</head>


# <a href="#"><i class="fas fa-question-circle"></i><b> Pregunta 2</b></a>{.tabset}


<i class="fas fa-book"></i> Librarías
-------------
```{r}
library(quantmod)
library(dplyr)
library(plotly)
library(gridExtra)
library(tidyverse)
library(tidyquant)
library(forcats)
library(devtools)
```



<i class="fas fa-code"></i> Función
-------------

```{r}
acciones <- c("AAPL","MSFT")
data <- tq_get(acciones,
               get = "stock.prices",
               from = "2000-01-01",
               to  = "2018-08-30",
               periodicity = "monthly")
data <- data.frame(data$symbol, data$date, data$close)
data <- data%>%rename(accion=data.symbol,
                      fecha=data.date,
                      precio=data.close)
finance = function(x,return=c('yes','no'),plot=c('type 1','type 2'),normal=c('yes','no')){
  
  #retornos log
  if (return=='yes'){
    retornoslog <- x %>%
      group_by(accion) %>%
      tq_transmute(select = precio,
                   mutate_fun = periodReturn,
                   period = "monthly",
                   type = "log",
                   col_rename = "retornos")
    dataA <- subset(retornoslog, accion=="AAPL")
    dataM <- subset(retornoslog, accion=="MSFT")
    dataA <- dataA %>% mutate(retcumA = cumsum(retornos))
    dataM <- dataM %>% mutate(retcumM = cumsum(retornos)) 
    
    #grafico 11:retornos log
    ifelse(plot=='type 1',
           g11 <- plot_ly(dataA, x = ~fecha) %>%
             add_lines(y = ~dataA$retornos, name = "APPLE", line = list(color = 'rgb(19,135,171)', width = 2)) %>% 
             add_lines(y = ~dataM$retornos, name = "MICROSOFT", line = list(color = 'rgb(153,171,254)', width = 2)) %>%
             layout(
               title = "RETORNOS (logarítmicos) APPLE & MICROSOFT",
               xaxis = list(
                 rangeselector = list(
                   buttons = list(
                     list(
                       count = 3,
                       label = "3 mo",
                       step = "month",
                       stepmode = "backward"),
                     list(
                       count = 6,
                       label = "6 mo",
                       step = "month",
                       stepmode = "backward"),
                     list(
                       count = 1,
                       label = "1 yr",
                       step = "year",
                       stepmode = "backward"),
                     list(
                       count = 1,
                       label = "YTD",
                       step = "year",
                       stepmode = "todate"),
                     list(step = "all"))),
                 
                 rangeslider = list(type = "Fecha")),
               yaxis = list(title = "Retornos")),
           
           ifelse(
             plot=='type 2',
                  g12 <- plot_ly(dataA, x = ~fecha) %>%
                    add_lines(y = ~dataA$retcumA, name = "APPLE", line = list(color = 'rgb(19,135,171)', width = 2)) %>% 
                    add_lines(y = ~dataM$retcumM, name = "MICROSOFT", line = list(color = 'rgb(153,171,254)', width = 2)) %>%
                    layout(
                      title = "RETORNOS ACUMULADOS (logarítmicos) APPLE & MICROSOFT",
                      xaxis = list(
                        rangeselector = list(
                          buttons = list(
                            list(
                              count = 3,
                              label = "3 mo",
                              step = "month",
                              stepmode = "backward"),
                            list(
                              count = 6,
                              label = "6 mo",
                              step = "month",
                              stepmode = "backward"),
                            list(
                              count = 1,
                              label = "1 yr",
                              step = "year",
                              stepmode = "backward"),
                            list(
                              count = 1,
                              label = "YTD",
                              step = "year",
                              stepmode = "todate"),
                            list(step = "all"))),
                        
                        rangeslider = list(type = "Fecha")),
                      
                      yaxis = list(title = "Retornos"))
           )#ifelse dentro de los graficos
    )#fin ifelse graficos 
  
    jlog = by(retornoslog,retornoslog$accion,
              function(x){
                n=length(x$retornos)
                mean = sum(x$retornos)/n
                skewness = ((sum(x$retornos-mean)^3)/n)/((sum(x$retornos-mean)^2)/n)^(3/2)
                kurtosis = ((sum(x$retornos-mean)^4)/n)/((sum(x$retornos-mean)^2)/n)^2
                JB = n*(((skewness^2)/6)+(((kurtosis-3)^2)/24))
                j = paste('p-value =',1 - pchisq(JB,df = 2),ifelse(1 - pchisq(JB,df = 2)<0.05,
                                                                   ', se rechaza la hipotesis nula de normalidad para los retornos de Apple',
                                                                   ', no se rechaza la hipotesis nula de normalidad para los retornos de Microsoft'))})
    }#fin primer if si return=yes
  #retornos aritmeticos
  else if (return=='no'){
    retornosimple <- x %>% 
      group_by(accion) %>%
      tq_transmute(select = precio,
                 mutate_fun = periodReturn,
                 period = "monthly",
                 type = "arithmetic",
                 col_rename = "retornos")
    dataA1 <- subset(retornosimple, accion=="AAPL")
    dataM1 <- subset(retornosimple, accion=="MSFT")
    dataA1 <- dataA1 %>% mutate(retcumA = cumsum(retornos))
    dataM1 <- dataM1 %>% mutate(retcumM = cumsum(retornos))
    
    
    ifelse(plot=='type 1',
           g21 <- plot_ly(dataA1, x = ~fecha) %>%
             add_lines(y = ~dataA1$retornos, name = "APPLE", line = list(color = 'rgb(19,135,171)', width = 2)) %>% 
             add_lines(y = ~dataM1$retornos, name = "MICROSOFT", line = list(color = 'rgb(153,171,254)', width = 2)) %>%
             layout(
               title = "RETORNOS (aritméticos) APPLE & MICROSOFT",
               xaxis = list(
                 rangeselector = list(
                   buttons = list(
                     list(
                       count = 3,
                       label = "3 mo",
                       step = "month",
                       stepmode = "backward"),
                     list(
                       count = 6,
                       label = "6 mo",
                       step = "month",
                       stepmode = "backward"),
                     list(
                       count = 1,
                       label = "1 yr",
                       step = "year",
                       stepmode = "backward"),
                     list(
                       count = 1,
                       label = "YTD",
                       step = "year",
                       stepmode = "todate"),
                     list(step = "all"))),
                 
                 rangeslider = list(type = "Fecha")),
               
               yaxis = list(title = "Retornos")),
           ifelse(plot=='type 2',
                  g22 <- plot_ly(dataA1, x = ~fecha) %>%
                    add_lines(y = ~dataA1$retcumA, name = "APPLE", line = list(color = 'rgb(19,135,171)', width = 2)) %>% 
                    add_lines(y = ~dataM1$retcumM, name = "MICROSOFT", line = list(color = 'rgb(153,171,254)', width = 2)) %>%
                    layout(
                      title = "RETORNOS ACUMULADOS (aritméticos) APPLE & MICROSOFT",
                      xaxis = list(
                        rangeselector = list(
                          buttons = list(
                            list(
                              count = 3,
                              label = "3 mo",
                              step = "month",
                              stepmode = "backward"),
                            list(
                              count = 6,
                              label = "6 mo",
                              step = "month",
                              stepmode = "backward"),
                            list(
                              count = 1,
                              label = "1 yr",
                              step = "year",
                              stepmode = "backward"),
                            list(
                              count = 1,
                              label = "YTD",
                              step = "year",
                              stepmode = "todate"),
                            list(step = "all"))),
                        
                        rangeslider = list(type = "Fecha")),
                      
                      yaxis = list(title = "Retornos"))
                  )#fin ifelse grafico tipo 2
           ) #fin primer ifelse grafico tipo 1
    
    j_arit= by(retornosimple,retornosimple$accion,
               function(x){
                 n=length(x$retornos)
                 mean = sum(x$retornos)/n
                 skewness = ((sum(x$retornos-mean)^3)/n)/((sum(x$retornos-mean)^2)/n)^(3/2)
                 kurtosis = ((sum(x$retornos-mean)^4)/n)/((sum(x$retornos-mean)^2)/n)^2
                 JB = n*(((skewness^2)/6)+(((kurtosis-3)^2)/24))
                 j = paste('p-value =',1 - pchisq(JB,df = 2),
                           ifelse(1 - pchisq(JB,df = 2)<0.05,
                                  ', se rechaza la hipotesis nula de normalidad para los retornos de Apple',
                                  ', no se rechaza la hipotesis nula de normalidad para los retornos de Microsoft'))})
    }#fin else if retornos=no
  
  #debemos general el resultado normal==no y dado que en ambos casos se realiza el test, programamos la salida:
  no="Se realizó test de Normalidad, ocultando su resultado"
  
  #debemos generar todas las posibles salidas
  ifelse(return=="yes"& plot=='type 1' & normal=="yes",return(list(g11,jlog)),
         ifelse(return=='yes' & plot=='type 2' & normal=="yes",return(list(g12,jlog)),
                ifelse(return=='yes' & plot=='type 1' & normal=="no",return(list(g11,no)),
                       ifelse(return=='yes' & plot=='type 2' & normal=="no",return(list(g12,no)),
                              ifelse(return=='no' & plot=='type 1' & normal=="yes",return(list(g21,j_arit)),
                                     ifelse(return=='no' & plot=='type 2' & normal=="yes",return(list(g22,j_arit)),
                                            ifelse(return=='no' & plot=='type 1' & normal=="no",return(list(g21,no)),
                                                   ifelse(return=='no' & plot=='type 2' & normal=="no",return(list(g22,no))))))))
                
         ))
  
  
  }#fin funcion
```




<i class="fas fa-chart-line"></i> Resultados
--------------
```{r fig.asp=0.5, fig.height=15, fig.width=10}
finance(data,"yes","type 1","yes")
finance(data,"no","type 1","yes")
finance(data, "yes", "type 2", "yes")
finance(data, "no", "type 2", "yes")
```



# <a href="#"><i class="fas fa-question-circle"></i> <b>Pregunta 3</b></a>{.tabset - .tabset-fade}


--------------